Certifications in the Era of AI
AI tools are now capable of generating network configurations, explaining protocols, summarizing logs, and guiding users through troubleshooting processes. An engineer can request assistance from an AI to configure BGP, construct a VXLAN EVPN fabric, or diagnose a DNS issue. The tool delivers a response within seconds.
While these capabilities are impressive, they prompt an important question: If AI can perform many tasks previously handled manually by engineers, do certifications still hold value? The answer depends on the original intent behind certifications.
What Certifications Were Meant to Do
Certifications were never meant to prove someone could memorize commands. At least not the good ones.
Their purpose was to demonstrate a working understanding of systems and protocols. A routing certification demonstrates that an engineer understands how routes traverse a network. A security certification shows that the engineer understands vulnerability points and defense models. Cloud certifications show how distributed systems are designed and operated.
They also create a shared language. When two engineers both understand BGP attributes or subnetting, they can diagnose issues together without starting from scratch.
What AI Actually Changes
AI is very good at assisting with execution. It can write configurations, summarize documentation, suggest commands, and analyze logs. Those are useful capabilities. They save time and reduce headbanging.
But AI does not change the nature of the systems themselves. BGP still behaves like BGP. TCP still behaves like TCP. Routing loops and broadcast storms still happen the same way they always have. AI accelerates doing the work. It does not replace understanding the system. An engineer who understands the protocol can use AI as a helpful assistant. An engineer who does not understand the protocol will simply paste the answer and hope it works. Hope is not a network design strategy.
The Rise of Copy-Paste Engineering
One likely outcome of AI is something we might call copy-paste engineering.
An engineer asks an AI for a configuration. The AI produces something that looks correct. The engineer pastes it into a router or firewall. The system comes up and traffic flows. Then it breaks. Maybe a route policy leaks a prefix. Maybe a firewall rule exposes something it shouldn’t. Maybe a VXLAN fabric behaves oddly when a link fails. At that point the real question appears: does the engineer understand what was just built?
AI can generate solutions, but it cannot ensure operational expertise. Network failures often occur in unexpected ways, necessitating engineers who comprehend the underlying mechanics of configurations.
Why Certifications May Become More Important
Many people assume AI will make certifications less valuable. The opposite may happen.
As AI tools become common, the ability to evaluate AI output becomes critical. Someone has to recognize when the generated configuration is correct and when it is subtly wrong. That requires understanding the fundamentals.
Employers will continue to require engineers who understand the significance of BGP attributes, control plane behavior, and network scaling limitations. While AI can expedite configuration tasks, it cannot assume responsibility for network integrity. Certifications remain a key indicator of foundational knowledge.
Certifications Will Probably Change
The certifications themselves will likely evolve. Older certification exams often rewarded memorizing commands or vendor-specific syntax. That approach made sense when the command line was the primary interface for network operations. The industry is shifting toward automation, APIs, and infrastructure defined in code. AI will likely become another layer in that workflow.
Future certifications may focus less on recalling commands and more on understanding architecture and failure scenarios. Engineers may need to review configurations, identify design flaws, or explain how protocols behave under stress.
I also expect certifications to become very “AI-heavy” as part of marketing hype. Vendors will be throwing AI around like they already do. This AI-heavy webpage and push will make it into certifications.
Who Will Struggle in the AI Era
Two categories of engineers may encounter challenges in the AI era.
The first is the memorization engineer. This person knows commands but lacks deep understanding. If AI can generate commands instantly, that advantage disappears.
The second group includes engineers who are overly dependent on AI for decision-making and do not develop the necessary foundational knowledge.
Both approaches break down when systems behave in unpredicted ways. Networks eventually do strange things. When that happens, someone has to understand the mechanics well enough to diagnose the problem. AI can assist with troubleshooting. It cannot replace the engineer responsible for the network.
Who Will Thrive
The engineers who succeed will combine three things: fundamentals, experience, and AI tools. These engineers will prioritize understanding protocols before leveraging AI to streamline routine tasks. They will critically review AI-generated output, adapt it to specific environments, and deploy solutions confidently. When failures occur, they will possess the skills to systematically diagnose issues. In this framework, AI serves as a productivity enhancer rather than a substitute for expertise.
For those at the beginning of their careers, certifications remain an effective means of acquiring foundational knowledge. They offer structured learning and introduce topics that might otherwise be overlooked.
For experienced professionals, certifications can formalize existing knowledge and address gaps. Even seasoned engineers may uncover areas for improvement. The primary value lies in the learning process, rather than the certification badge itself.
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